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A run can take a long time and sends many requests to the API along the way.
If it stops in the middle (e.g. due to a crash, Ctrl+C, or an API error)
all the work done so far is lost. You have to start over from scratch, which
costs time and API budget.
Idea
AutoRecLab already saves the state of the tree search (as a pickled search
state). We could use this saved state to continue an interrupted run from
exactly the point where it stopped, instead of starting over.
For example via a flag:
autoreclab --resume <run-folder>
The agent then loads the last saved state and continues from there.
Benefits
Saves time on long experiments
Saves API costs, because already completed steps are not repeated
Makes the tool more robust against crashes and connection errors
Questions for discussion
Should resume happen automatically (the last run is simply continued), or
explicitly via a flag (--resume)?
How often should the state be saved: after every step, or only at certain
intervals?
Is it enough to continue from the last state, or would it be useful to also
restart from an earlier point?
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Idea: Resume interrupted runs (Checkpoint)
Problem
A run can take a long time and sends many requests to the API along the way.
If it stops in the middle (e.g. due to a crash, Ctrl+C, or an API error)
all the work done so far is lost. You have to start over from scratch, which
costs time and API budget.
Idea
AutoRecLab already saves the state of the tree search (as a pickled search
state). We could use this saved state to continue an interrupted run from
exactly the point where it stopped, instead of starting over.
For example via a flag:
The agent then loads the last saved state and continues from there.
Benefits
Questions for discussion
explicitly via a flag (
--resume)?intervals?
restart from an earlier point?
All reactions